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The access to ever-increasing super-computing facilities, combined with the availability of huge data repositories (although largely unannotated), has permitted the emergence of a significant trend with pure data-driven deep learning approaches. However, these methods only loosely take into account the nature and structure of the processed data. We believe that it is important to rather build hybrid deep learning methods by integrating our prior knowledge about the nature of the processed data, their generation process or if possible their perception by humans. We will illustrate the potential of such model-based deep learning approaches (or hybrid deep learning) for music analysis and synthesis.
Music indexing allows the finding of music excerpts among a large music catalog and the detection of duplicates. With the rise of social media, it is more and more important for music owners to detect misuse and illegal use of their music.
16 novembre 2023 51 min
"Basic-pitch" is a lightweight neural network for musical instrument transcription, which supports polyphonic outputs and generalizes to a wide variety of instruments (including vocals). In this talk, we will discuss how we built and evalua
16 novembre 2023 43 min
16 novembre 2023 05 min
Music Streaming Services such as Deezer offer their users a catalog of tens of millions of songs. Navigating through such a vast catalog requires retrieving and organizing musical knowledge in an automated way using music information retrie
16 novembre 2023 01 h 04 min
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1, place Igor-Stravinsky
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Du lundi au vendredi de 9h30 à 19h
Fermé le samedi et le dimanche
Hôtel de Ville, Rambuteau, Châtelet, Les Halles
Institut de Recherche et de Coordination Acoustique/Musique
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